Changeset 101 for trunk/examples/retina/benchmark_linear.py

Timestamp:

01/15/08 17:44:22 (4 years ago)

Author:

LaurentPerrinet

Message:

Finished examples of use of NeuroTools: retina / renamd SpikeTrain.mean_firing_rate to SpikeTrain.mean_rate for consistency with SpikeList.mean_rate / bugfix in spikes.py for the definition of a range in SpikeTrain.mean_rate

Files:

• trunk/examples/retina/benchmark_linear.py (modified) (5 diffs)

trunk/examples/retina/benchmark_linear.py

@@ -17 +17 @@
 import retina as model
 import NeuroTools.benchmark as benchmark
-
-
 
 
@@ -43 +41 @@
 
     N, N_ret, simtime = params['N'], params['N_ret'], params['simtime']
-    N_smooth = 100 # how many time bins
+    t_smooth = 100. #  smooting time (ms)
 
     for experiment in experiment_list:
@@ -50 +48 @@
         except:
             print "Loading data for experiment " , experiment
-            out_ON_DATA = benchmark.get('out',experiment)['out_ON_DATA']
-            # ON
-            temporal_ON , lower_edges = numpy.histogram(out_ON_DATA.as_list_id_list_time()[1],
-                                        bins=N_smooth, range=(out_ON_DATA.t_start,out_ON_DATA.t_stop))
-            temporal_ON /= N**2
-            # OFF : noit very useful here
-            #out_OFF_DATA = benchmark.get('out',experiment)['out_OFF_DATA']
-##            temporal_OFF , lower_edges = numpy.histogram(out_OFF_DATA.as_list_id_list_time()[1],
-##                                        bins=N_smooth, range=(out_ON_DATA.t_start,out_ON_DATA.t_stop))
-##            temporal_OFF /= N**2
+            out_ON = benchmark.get('out',experiment)['out_ON_DATA']
+
             # storing
             benchmark.put('firing_rate',{
-                    'temporal_ON' : temporal_ON,
-##                    'temporal_OFF' : temporal_OFF,
-                    'lower_edges' : lower_edges,
+                    'temporal_ON' : sum(out_ON.firing_rate(t_smooth))/N,
+                    #'temporal_OFF' : out_OFF.firing_rate(t_smooth),
+                    'lower_edges' : out_ON.time_axis(t_smooth),
                     'firing_rate_ok' : True # a flag to do it once
                       }, experiment )
@@ -89 +79 @@
     #pylab.legend()
 
-    pylab.savefig(benchmark.filename + '/benchmark_linear.png') #, dpi=300) #
+    pylab.savefig(benchmark.filename + '/benchmark_linear.pdf') #, dpi=300) #
 
 
 if __name__ == '__main__':
 
-    # not working tag= '07-02-16'
-    # tag= '07-02-14'
-    # tag= '07-02-23'
-    tag= '07-02-27'
-    tag = '07-03-08'
-    tag = '07-05-09'
     tag = 'test'
 
@@ -106 +90 @@
 
     ret = model.Retina(21)
-    ret.params['simtime'] = 4000*0.1
-    ret.params['amplitude'] = numpy.ones((ret.params['N'],ret.params['N'] ))
-
-    run = benchmark.get_experiment_dict({'snr' : 10.**(numpy.linspace(-.50,.75,5))})
-
+    #ret.params['simtime'] = 4000*0.1
+    ret.params['amplitude'] = numpy.ones(ret.params['N'])
+    N_exp = 15
+    snr  = ret.params['snr']* numpy.linspace(0.1,2.0,N_exp)
+    run = benchmark.get_experiment_dict({'snr':snr})
+    print snr#,ret.params
     B = benchmark.Benchmark(filename,ret,run)
 
     B.run_simulations()
     show(B)
-
+    #B.reset_all()